We investigate the performance of a reconfigurable intelligent surface (RIS) assisted single-input single-output (SISO) communication system where RIS elements are narrowly spaced so that the channels between the RIS elements and receiver are spatially correlated. Adjacent RIS elements are grouped together to reduce the channel estimation overhead. The statistical properties of the optimal received SNR are analytically derived and these are used to characterize the coverage probability of the system. An analytical upper bound for the average achievable rate is also derived. This analysis provides insight into the impact of the grouping strategy and element spatial channel correlation level on the coverage probability and the achievable rate of the system. Numerical results validate the tightness of the closed-form expressions. Our results show that the average achievable rate for a given group size is higher for the spatially correlated RIS elements as compared to the uncorrelated configuration. 

Performance Analysis of RIS-Assisted Communications With Element Grouping and Spatial Correlation

A design for a highly reconfigurable intelligent surface (RIS) that can provide 3-D passive reflective beamforming suitable for sub-6-GHz frequency bands is proposed. The RIS is based on a novel double-layer structure consisting of independently controllable and highly reconfigurable elements on top of a ground plane. The novelty of the structure is the use of reconfigurable RIS elements, whose size is of the order of a wavelength, which are optimized to function over wide incident and reflected angles. In addition, the individual elements each have four RF switches, in a 5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> 5 subelement structure, providing 16 different reflective phases, from 0° to 360° relative to the incident waves. To quantify the performance of RIS, the performance metric of phase entropy is defined and it is also used as an objective function for optimizing the design. An efficient analytical method for predicting the reflected waves from the RIS elements, as well as phase entropy, is also provided. For verification, a prototype of a 4 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> 4-element RIS, with a total size of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.32\,\,\textrm {m}\,\,\times \,\,0.34\,\,\textrm {m}$ </tex-math></inline-formula> , is fabricated and an experimental setup for measuring the scattered pattern is described. It is shown that waves incident from various angles can be passively beam steered to any angle within 0°–360° azimuth and ±50° elevation angles. The high reconfigurability to manipulate incident waves makes the proposed RIS a promising surface for use in future high-capacity communication systems. 

https://www.techrxiv.org/articles/preprint/A_Novel_Reconfigurable_Intelligent_Surface_for_Wide-Angle_Passive_Beamforming/19755034/2/files/35211211.pdf

A Novel Reconfigurable Intelligent Surface for Wide-Angle Passive Beamforming

Reconfigurable intelligent surface (RIS) enables the configuration of the propagation environment. Channel estimation is an essential task in realizing the RIS-aided communication system. A RIS-aided multi-user multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) communication system involves cascaded channels with high dimensions and sophisticated statistics. Thus, implementing the optimal minimum mean square error (MMSE) with the integration computation is infeasible in practice. To accurately estimate channels with high accuracy in a RIS-aided multi-user MIMO-OFDM system, we model the channel state information (CSI) estimation as an image super-resolution (SR) problem to recover and denoise the channel matrix. Particularly, a convolutional neural network based on a super-resolution convolutional neural network (SRCNN) and denoising convolutional neural network (DnCNN), named SRDnNet, is then proposed. By taking estimated channels at pilot positions as a low-resolution image, the enhanced SRCNN can fully exploit the features of inputs to learn a suitable interpolation method and generate the coarse estimation of the channel matrix. The denoising model DnCNN with an element-wise subtraction structure can exploit features of the additive noise and recover channel coefficients from the coarse channel matrix. The simulation results demonstrate the effectiveness and excellent performance of the proposed SRDnNet. 

Deep Learning for Super-Resolution Channel Estimation in Reconfigurable Intelligent Surface Aided Systems

Active reconfigurable intelligent surfaces (RISs) have recently been proposed to complement and generalize passive RIS. In this work, the design for an active RIS based on phase-reconfigurable reflection amplifiers is proposed. The proposed active RIS elements’ design consists of a two-layer patch antenna and a phase-reconfigurable reflection amplifier that is realized by a cascade of a phase shifter and a reflection amplifier. Theoretical and numerical analyses are used to quantify key parameters that need to be met in the design of the reflection amplifier and phase shifters. These show that a tradeoff between the reflection amplifier’s gain and the phase shifter’s return and insertion loss is required to be balanced to obtain a stable and effective overall design. In particular, a reflection amplifier with about 13-dB gain and a 2-bit phase shifter with only about 1.9-dB insertion loss and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$-$</tex-math> </inline-formula> 25-dB return loss are designed. The final RIS element obtains 8.5-dB gain with four reconfigurable phases ranging from 0 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{\circ}$</tex-math> </inline-formula> to 360 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{\circ}$</tex-math> </inline-formula> with small root mean square (rms) gain and phase errors. An active RIS can be constructed by concatenating these elements together, and an efficient analytical method to calculate the scattered pattern by the active RIS is also proposed. Experimental results for a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2$</tex-math> </inline-formula> <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times$</tex-math> </inline-formula> <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2$</tex-math> </inline-formula> element active RIS prototype are also provided. These show that the active RIS provides received powers around 8.5 dB higher than that from using an equivalent passive RIS. The results demonstrate the feasibility of achieving gain in active RISs and help demonstrate their promise as a technology for future high-capacity wireless communication systems. 

An Active Reconfigurable Intelligent Surface Utilizing Phase-Reconfigurable Reflection Amplifiers

Reconfigurable intelligent surface (RIS) is regarded as a promising technology with great potential to boost wireless networks. Affected by the “double fading” effect, however, conventional passive RIS cannot bring considerable performance improvement when users are not close enough to RIS. Recently, active RIS is introduced to combat the double fading effect by actively amplifying incident signals with the aid of integrated reflection-type amplifiers. In order to reduce the hardware cost and energy consumption due to massive active components in the conventional fully-connected active RIS, a novel hardware-and-energy efficient sub-connected active RIS architecture has been proposed recently, in which multiple reconfigurable electromagnetic elements are driven by only one amplifier. In this paper, we first develop an improved and accurate signal model for the sub-connected active RIS architecture. Then, we investigate the joint transmit precoding and RIS reflection beamforming (i.e., the reflection phase-shift and amplification coefficients) designs in multiuser multiple-input single-output (MU-MISO) communication systems. Both sum-rate maximization and power minimization problems are solved by leveraging fractional programming (FP), block coordinate descent (BCD), second-order cone programming (SOCP), alternating direction method of multipliers (ADMM), and majorization-minimization (MM) methods. Extensive simulation results verify that compared with the conventional fully-connected structure, the proposed sub-connected active RIS can significantly reduce the hardware cost and power consumption, and achieve great performance improvement when power budget at RIS is limited. 

/pdf/joint-beamforming-designs-for-active-reconfigurable-1x09osy3.pdf

Joint Beamforming Designs for Active Reconfigurable Intelligent Surface: A Sub-Connected Array Architecture

The channel estimation overhead of reconfigurable intelligent surface (RIS) assisted communication systems can be prohibitive. Prior works have demonstrated via simulations that grouping neighbouring RIS elements can help to reduce the pilot overhead and improve achievable rate. In this paper, we present an analytical study of RIS element grouping. We derive a tight closed-form upper bound for the achievable rate and then maximize it with respect to the group size. Our analysis reveals that more coarse-grained grouping is important-when the channel coherence time is low (high mobility scenarios) or the transmit power is large. We also demonstrate that optimal grouping can yield significant performance improvements over simple `On-Off' RIS element switching schemes that have been recently considered.

Zan Li

Papers

Optimal Grouping Strategy for Reconfigurable Intelligent Surface Assisted Wireless Communications